Title page for ETD etd-0505103-123753

Document Type thesis

Author Name Murphy, Brian R

URN etd-0505103-123753

Title Order-sensitive XML Query Processing Over Relational Sources

Degree MS

Department Computer Science

Advisors
Elke Rundensteiner, Advisor
Lee Becker, Reader
Micha Hofri, Department Head

Keywords
computation pushdown
XML
Order-based Xquery processing
relational database
ordered SQL queries
data model mapping
XQuery
XML data mapping
SQL
XML algebra rewrite rules
XML document order

Date of Presentation/Defense 2003-04-17

Availability unrestricted

Abstract
XML is an emerging standard format for data on the Web as well as in
business applications. In order to store and access this information in an
efficient manner, database technology must be utilized. A relational
database system, the most established and mature technology for query processing and
storage, creates a strong foundation for such an XML data management system.
However, while relational databases are based on SQL queries, the original user
queries are written in XQuery, an XML query language. This XML query
language has support for order-sensitive queries as XML is an order-sensitive
markup language.

A major problem has been discovered with loading XML in a relational
database. That problem is the lack of native SQL support for and management
of order handling. While XQuery has order and positional support, SQL does not
have the same support.
For example, individuals who were viewing XML information about music
albums would have a hard time querying for the first three songs of a track list
from a relational
backend. Mapping XML documents to relational backends also proves hard
as the data models (hierarchical elements versus flat tables) are so different.

For these reasons, and other purposes, the Rainbow System is
being developed at WPI as a system that bridges XML data and relational data.
This thesis in particular deals
with the algebra operators that affect order, order sensitive loading and
mapping of XML documents, and the pushdown of order handling into SQL-capable
query engines. The
contributions of the thesis are the order-sensitive rewrite rules, new
XML to relational mappings with different order styles, order-sensitive
template-driven SQL generation, and a proposed metadata table for order-sensitive information.
A system that implements these proposed techniques with XQuery as the XML query language and
Oracle as the backend relational storage system has been developed. Experiments were created
to measure execution time based on various factors. First, scalability
of the system as backend data set size grows is studied. Second, scalability of the
system as results returned from the database grows, and finally, query execution
times with different loading types are explored. The experimental results are
encouraging. Query execution with the relational backend proves to be
much faster than native execution within the Rainbow system. These results
confirm the practical utility of our proposed order-sensitive XQuery execution solution
over relational data.

Files
brianmurphyMSthesis.pdf

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Document Type	thesis
Author Name	Murphy, Brian R
URN	etd-0505103-123753
Title	Order-sensitive XML Query Processing Over Relational Sources
Degree	MS
Department	Computer Science
Advisors	Elke Rundensteiner, Advisor Lee Becker, Reader Micha Hofri, Department Head
Keywords	computation pushdown XML Order-based Xquery processing relational database ordered SQL queries data model mapping XQuery XML data mapping SQL XML algebra rewrite rules XML document order
Date of Presentation/Defense	2003-04-17
Availability	unrestricted
Abstract XML is an emerging standard format for data on the Web as well as in business applications. In order to store and access this information in an efficient manner, database technology must be utilized. A relational database system, the most established and mature technology for query processing and storage, creates a strong foundation for such an XML data management system. However, while relational databases are based on SQL queries, the original user queries are written in XQuery, an XML query language. This XML query language has support for order-sensitive queries as XML is an order-sensitive markup language. A major problem has been discovered with loading XML in a relational database. That problem is the lack of native SQL support for and management of order handling. While XQuery has order and positional support, SQL does not have the same support. For example, individuals who were viewing XML information about music albums would have a hard time querying for the first three songs of a track list from a relational backend. Mapping XML documents to relational backends also proves hard as the data models (hierarchical elements versus flat tables) are so different. For these reasons, and other purposes, the Rainbow System is being developed at WPI as a system that bridges XML data and relational data. This thesis in particular deals with the algebra operators that affect order, order sensitive loading and mapping of XML documents, and the pushdown of order handling into SQL-capable query engines. The contributions of the thesis are the order-sensitive rewrite rules, new XML to relational mappings with different order styles, order-sensitive template-driven SQL generation, and a proposed metadata table for order-sensitive information. A system that implements these proposed techniques with XQuery as the XML query language and Oracle as the backend relational storage system has been developed. Experiments were created to measure execution time based on various factors. First, scalability of the system as backend data set size grows is studied. Second, scalability of the system as results returned from the database grows, and finally, query execution times with different loading types are explored. The experimental results are encouraging. Query execution with the relational backend proves to be much faster than native execution within the Rainbow system. These results confirm the practical utility of our proposed order-sensitive XQuery execution solution over relational data.
Files	brianmurphyMSthesis.pdf